OLTPShare: The case for sharing in OLTP workloads

Research output: Contribution to journalConference articleContributedpeer-review

Contributors

  • Robin Rehrmann - , Chair of Databases, SAP Research (Author)
  • Carsten Binnig - , Technische Universität Darmstadt (Author)
  • Alexander Böhm - , SAP Research (Author)
  • Kihong Kim - , SAP Labs Korea (Author)
  • Wolfgang Lehner - , Chair of Databases (Author)
  • Amr Rizk - , Technische Universität Darmstadt (Author)

Abstract

In the past, resource sharing has been extensively studied for OLAP workloads. Naturally, the question arises, why studies mainly focus on OLAP and not on OLTP workloads? At first sight, OLTP queries - due to their short runtime - may not have enough potential for the additional overhead. In addition, OLTP workloads do not only execute read operations but also updates. In this paper, we address query sharing for OLTP workloads. We first analyze the sharing potential in real-world OLTP workloads. Based on those findings, we then present an execution strategy, called OLTPShare that implements a novel batching scheme for OLTP workloads. We analyze the sharing benefits by integrating OLTPShare into a prototype version of the commercial database system SAP HANA. Our results show for different OLTP workloads that OLTPShare enables SAP HANA to provide a significant throughput increase in high-load scenarios compared to the conventional execution strategy without sharing.

Details

Original languageEnglish
Pages (from-to)1769-1780
Number of pages12
JournalProceedings of the VLDB Endowment
Volume11
Issue number12
Publication statusPublished - 2018
Peer-reviewedYes

Conference

Title44th International Conference on Very Large Data Bases, VLDB 2018
Duration27 - 31 August 2018
CityRio de Janeiro
CountryBrazil

External IDs

Scopus 85058888857
ORCID /0000-0001-8107-2775/work/142253504